Chromosome X plays a distinctive and notable role in human health and disease, but there is a fundamental gap in studying its function in complex human disease, because the vast majority of genome-wide association studies (GWAS) disregarded or incorrectly analyzed X-linked data. Hence, there is an urgent need for methods that will enable investigation of the X-linked basis of complex diseases, especially those that exhibit gender disparity in risk, age of onset, severity, o symptoms. Such methods must account for differences between chromosome X and the rest of the genome, including differences in the modes of inheritance, sexual dimorphism in susceptibility, dosage compensation (X-inactivation), population genetic patterns, and ascertainment biases. The overarching long-term goal of the research program is to improve the search for sex-linked complex disease genes and to elucidate how evolutionary history has shaped human genetic variation differently on the sex chromosomes. The objective of this application is to discover X-linked loci underlying various complex diseases while putting forth improved statistical and computational methods and software that are specially designed for chromosome X. The underlying rationale is that the proposed research will help uncover a portion of the heritable basis of complex disease that has yet to be explained by GWAS loci ('missing heritability'), reveal the role of chromosome X in disease etiology, and advance the exploration of the sex-linked basis of sex-specific disease patterns. Guided by extensive preliminary data and analysis, this objective will be met by pursuing three specific aims: (1) Develop new statistical and computational methodologies to facilitate powerful association studies that accommodate chromosome X; (2) Discover and replicate X-linked disease genes in existing and emerging GWAS datasets spanning different diseases and populations; (3) develop a software package for X-linked association studies. The innovation of the proposed research stems from the novel analytical methodologies that accurately deal with the challenges surrounding the analysis of chromosome X. Its contribution will be significant because it will bring chromosome X-which has so far been largely omitted-into the GWAS landscape and, specifically, will find novel X-linked associations underlying complex human disease while making analytical methods available for the next generation of association studies. This contribution will be further multiplied by offering a software package implementing all methods to the scientific community, thus allowing researchers to uncover X-linked genes underlying additional complex diseases and in additional populations. Collectively, the proposed research is significant as it will substantially advance our understanding of the role chromosome X plays in complex human disease.